Glossary
Searchable terminology from accessibility, web standards, and related fields.
77 results found in ethics.
- AI Accountability (Algorithmic Accountability, AI Governance)
- The principle that developers, deployers, and operators of AI systems should be held responsible for the outcomes those systems produce, including negative effects on marginalized populations such as …
- AI Fairness (Algorithmic Fairness, Fair AI)
- The principle that AI systems should not create or reinforce unfair bias against particular groups. Standard AI fairness frameworks primarily address race and gender but are increasingly recognized as…
- AI Hallucination (Model Hallucination, Confabulation)
- The phenomenon where an AI model generates confident, plausible-sounding responses that are factually incorrect, fabricated, or not grounded in the actual input data. In accessibility contexts, AI hal…
- AI Incident Database (AIID, AI Incident Tracker)
- A publicly accessible repository that documents reported incidents where AI-driven systems have caused harm or produced negative outcomes for individuals, communities, or society. Major databases incl…
- AI Recourse (Algorithmic Recourse, AI Appeal Mechanism)
- The ability of individuals negatively affected by AI-driven decisions to challenge, appeal, or seek correction of those decisions. For people with disabilities, AI recourse is particularly critical be…
- AI disability representation (AI disability simulation, Disability representation in AI)
- The portrayal or simulation of disabled experiences, communication styles, or perspectives by artificial intelligence systems. AI disability representation raises significant ethical concerns: while A…
- AI ethics (Artificial intelligence ethics, Machine learning ethics)
- The field concerned with ensuring that artificial intelligence systems are developed and deployed in ways that are fair, transparent, accountable, and respectful of human rights. In accessibility cont…
- AI hallucination (Model hallucination, Confabulation)
- The generation of plausible-sounding but factually incorrect or fabricated information by AI systems, particularly large language and multimodal models. In accessibility applications, AI hallucination…
- AI sycophancy (Sycophantic AI, AI agreeableness bias)
- The tendency of AI systems, particularly large language models, to provide overly affirmative, agreeable, or encouraging responses that cater to the user rather than providing accurate information. In…
- AI transparency (Algorithmic transparency, Model transparency)
- The practice of making artificial intelligence systems understandable to users and stakeholders, including how they work, what data they use, and the confidence levels of their outputs. For assistive …
- Ability assumption in AI (Visual ability assumption, Sighted bias in AI)
- The tendency of AI systems to assume users possess typical sensory, cognitive, or physical abilities, leading to inappropriate responses or instructions. In the context of visual AI assistants for bli…
- Affective Computing (Emotion AI, Emotional AI)
- A field of AI that attempts to detect, interpret, and simulate human emotions using technologies such as facial expression analysis, voice tone detection, physiological sensors, and behavioral pattern…
- Algorithmic Bias (AI Bias, Machine Learning Bias)
- Systematic and unfair discrimination embedded in the outputs of algorithmic systems, arising from biased training data, flawed model design, or unrepresentative development processes. For people with …
- Algorithmic Discrimination (AI Discrimination, Automated Discrimination)
- The systematic disadvantaging of specific groups through the operation of AI-driven systems, whether intentional or emergent. For people with disabilities, algorithmic discrimination occurs across man…
- Algorithmic Harm (AI Harm, Algorithmic Negative Outcome)
- Any difficulty, disadvantage, or injury caused by the use of AI-driven systems, ranging from mere inconvenience to material harm. For people with disabilities, documented algorithmic harms include den…
- Algorithmic accountability (AI accountability)
- The principle that organizations and individuals responsible for creating and deploying algorithmic systems should be held responsible for the outcomes and impacts of those systems. In accessibility c…
- Algorithmic bias (AI bias, Machine learning bias, Algorithmic discrimination)
- Systematic and unfair errors in the outputs of automated decision-making systems that disadvantage particular groups of people. For people with disabilities, algorithmic bias arises from underrepresen…
- Anthropomorphism (Humanization, Anthropomorphization)
- The attribution of human characteristics, emotions, intentions, or behaviors to non-human entities such as technology, animals, or objects. In assistive technology and conversational AI design, anthro…
- Applied Behavioural Analysis (ABA, Applied Behavior Analysis)
- A therapeutic approach based on behaviorist principles that uses reinforcement and conditioning to modify behaviour, widely used with autistic children. ABA has become increasingly controversial withi…
- Bias Mitigation (Algorithmic Fairness, Debiasing)
- The process of identifying and reducing systematic errors or prejudices in AI systems, datasets, and algorithms that lead to unfair outcomes for particular groups of people. In accessibility, bias mit…